code: def test_predict_with_dataset(self):
      keras_model = self.create_model()
      model = KerasModel(keras_model)
  
      x, y = self.create_training_data()
      results_pre = model.evaluate(x, y)
  
      pred_y = np.argmax(
          np.array(
              model.predict(self.create_predict_dataset()).collect()
          ),
          axis=1,
      )
  
      acc = np.average((pred_y == y))
  
      assert np.square(acc - results_pre["acc"]) < 0.000001
  
imports: import pytest
  from bigdl.orca.test_zoo_utils import ZooTestCase
  import tensorflow
  import numpy
  import os
  from bigdl.orca.tfpark import KerasModel, TFDataset, TFOptimizer
label_desc: Use image node_id 20 for calling the TestTFParkModel obj's underlying member method code with example usage: obj.test_predict_with_dataset() without return types